MbrlCatalogueTitleDetail

Do you wish to reserve the book?
A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions
A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions
Hey, we have placed the reservation for you!
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Title added to your shelf!
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions
A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions

Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
How would you like to get it?
We have requested the book for you! Sorry the robot delivery is not available at the moment
We have requested the book for you!
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions
A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions
Journal Article

A Novel EEG-Based Assessment of Distraction in Simulated Driving under Different Road and Traffic Conditions

2024
Request Book From Autostore and Choose the Collection Method
Overview
The drivers’ distraction plays a crucial role in road safety as it is one of the main impacting causes of road accidents. The phenomenon of distraction encompasses both psychological and environmental factors and, therefore, addressing the complex interplay contributing to human distraction in automotive is crucial for developing technologies and interventions for improving road safety. In scientific literature, different works were proposed for the distraction characterization in automotive, but there is still the lack of a univocal measure to assess the degree of distraction, nor a gold-standard tool that allows to “detect” eventual events, road traffic, and additional driving tasks that might contribute to the drivers’ distraction. Therefore, the present study aimed at developing an EEG-based “Distraction index” obtained by the combination of the driver’s mental workload and attention neurometrics and investigating and validating its reliability by analyzing together subjective and behavioral measures. A total of 25 licensed drivers were involved in this study, where they had to drive in two different scenarios, i.e., City and Highway, while different secondary tasks were alternatively proposed in addition to the main one to modulate the driver’s attentional demand. The statistical analysis demonstrated the reliability of the proposed EEG-based distraction index in identifying the drivers’ distraction when driving along different roads and traffic conditions (all p < 0.001). More importantly, the proposed index was demonstrated to be reliable in identifying which are the most impacting additional driving tasks on the drivers’ distraction (all p < 0.01).